Measurement of soybean fatty acids by near-infrared spectroscopy: Linear and nonlinear calibration methods

A key element of successful development of new soybean cultivars is availability of inexpensive and rapid methods for measurement of FA in seeds. Published research demonstrated applicability of NIR spectroscopy for FA profiling in oilseeds. The objectives of this study were to investigate the applicability of NIR spectroscopy for measurement of FA in whole soybeans and compare performance of calibration methods. Equations were developed using partial least squares (PLS), artificial neural networks (ANN), and support vector machines (SVM) regression methods. Validation results demonstrated that (i) equations for total saturates had the highest predictive ability (r ²=0.91–0.94) and were usable for quality assurance applications, (ii) palmitic acid models (r ²=0.80–0.84) were usable for certain research applications, and (iii) equations for stearic (r ²=0.49–0.68), oleic (r ²=0.76–0.81), linoleic (r ²=0.73–0.76), and linolenic (r ²=0.67–0.74) acids could be used for sample screening. The SVM models produced significantly more accurate predictions than those developed with PLS. ANN calibrations were not different from the other two methods. Reduction in the number of calibration samples reduced predictive ability of all equations. The rate of performance degradation of SVM models with sample reduction was the lowest.     

Electrostatic capillary collector for in-situ spectroscopic analysis of aerosols

Identification of particulate matter is important in assessing an individual’s exposure to potentially harmful particles, such as aeroallergens, toxins, and emissions from combustion sources, which can contribute to cardio-pulmonary diseases. Efficient collection of aerosols is essential for aerosol exposure studies such as analysis of chemical and biological components. We present the design and evaluation of a capillary collector that collects PM_2.5 onto the outer surface of a capillary for in-situ spectroscopic analysis. The capillary collector uses a needle-to-ring corona generator to charge particles; the electric field between a cylinder and a wire inserted into the bore of a capillary is used to collect the charged particles. Corona and repelling voltages are optimized for maximum collection of ambient PM_2.5 particles and fluorescent polystyrene latex microspheres in the PM_2.5 size range, on the capillary. The capillary collection efficiency of ambient PM_2.5 at 3 slpm operating flow rate and optimal operating voltages is 63%. Fluorescence spectroscopy is used to quantify the collection of polystyrene latex microspheres. The fluorescence-based capillary collection efficiency is in close agreement with the capillary collection efficiency of ambient PM_2.5. The collection and analysis methodology can be used to develop a compact, low-cost sensor for in-situ spectroscopic analysis of aerosols to determine their chemical composition for source apportionment.

Copyright © 2019 American Association for Aerosol Research     

Crystallization behavior of polymer/montmorillonite nanocomposites. Part II. Intercalated poly(ε-caprolactone)/montmorillonite nanocomposites

The combination of surfactant modified montmorillonite (MMT) silicate layers, poly(ε-caprolactone) (PCL) and the adopted melt processing procedure results in intercalated nanocomposites in which the silicate layers act as nucleating agents for the crystallization of the PCL matrix and by which in turn the overall crystallization rate increases. At a sufficiently high MMT concentration and degree of supercooling the polymer-swollen silicate layer stacks disturb crystal growth, resulting in a decrease in the overall crystallization rate. Simultaneous, time resolved, synchrotron small and wide angle X-ray scattering experiments reveal that—when the retarding effect is absent at a sufficiently high temperature—the final semicrystalline structures of pure PCL and its nanocomposites are identical. The poorer nucleation in the case of pure PCL, however, results in a time wise smearing of primary and secondary crystallization whereas in the nanocomposites these events are well separated due to a nucleation induced, efficient and rapid primary crystallization. Secondary crystallization involves the insertion of new lamellar crystals in between the already existing ones.     

Verification of randomized consensus algorithms under round-rigid adversaries

International Journal on Software Tools for Technology Transfer - Randomized fault-tolerant distributed algorithms pose a number of challenges for automated verification: (i) parameterization in...     

Effects of Al:Si and (Al + Na):Si ratios on the properties of the international simple glass,part II: Structure

High-alumina containing high-level waste (HLW) will be vitrified at the Waste Treatment Plant at the Hanford Site. The resulting glasses, high in alumina, will have distinct composition-structure-property (C-S-P) relationships compared to previously studied HLW glasses. These C-S-P relationships determine the processability and product durability of glasses and therefore must be understood. The main purpose of this study is to understand the detailed structural changes caused by Al:Si and (Al + Na):Si substitutions in a simplified nuclear waste model glass (ISG, international simple glass) by combining experimental structural characterizations and molecular dynamics (MD) simulations. The structures of these two series of glasses were characterized by neutron total scattering and ²⁷Al, ²³Na, ²⁹Si, and ¹¹B solid-state nuclear magnetic resonance (NMR) spectroscopy. Additionally, MD simulations were used to generate atomistic structural models of the borosilicate glasses and simulation results were validated by the experimental structural data. Short-range (eg, bond distance, coordination number, etc) and medium-range (eg, oxygen speciation, network connectivity, polyhedral linkages) structural features of the borosilicate glasses were systematically investigated as a function of the degree of substitution. The results show that bond distance and coordination number of the cation-oxygen pairs are relatively insensitive to Al:Si and (Al + Na):Si substitutions with the exception of the B-O pair. Additionally, the Al:Si substitution results in an increase in tri-bridging oxygen species, whereas (Al + Na):Si substitution creates nonbridging oxygen species. Charge compensator preferences were found for Si-[NBO] (Na⁺), ^[3]B-[NBO] (Na⁺), ^[4]B (mostly Ca²⁺), ^[4]Al (nearly equally split Na⁺ and Ca²⁺), and ^[6]Zr (mostly Ca²⁺). The network former-BO-network former linkages preferences were also tabulated; Si-O-Al and Al-O-Al were preferred at the expense of lower Si-O-^[3]B and ^[3]B-O-^[3]B linkages. These results provide insights on the structural origins of property changes such as glass-transition temperature caused by the substitutions, providing a basis for future improvements of theoretical and computer simulation models.     

INSIGMA: an intelligent transportation system for urban mobility enhancement

Intelligent Transportation Systems (ITS) aim to improve safety, mobility and environmental performance of road transport. The INSIGMA project provides a fresh look at the possible innovations in this field, by enhancing the functionality and accuracy of ITS in urban environments. This paper describes the architecture, sensors, processing algorithms, output modules and advantages of the developed system. A comparison of existing ITS systems has been provided as background. Special attention has been given to performance and privacy issues, as the system includes social aspects such as location monitoring.     

The making of the Xian terra‐cotta soldiers

Abstract

This paper describes the making of a short film on the Xian terra‐cotta soldiers using our integrated HU‐MANOID software. The method of creating and animating the soldiers’ faces is first presented. Then, we show how our approach, based on metaballs and spline surfaces, was used for designing and deforming soldiers’ bodies. For the animation of the bodies, we describe the motion control methods. Clothes for the soldiers are then described as well as horses and decor design. For the rendering, we explained our strategy using parallel machines. Finally, problems of integration are addressed.     

A novel electromyographic signal simulator for muscle contraction studies

Mathematical simulation has been widely used in biomedical and biological sciences. In the case of the surface electromyographic (SEMG) activity, some models have been proposed aiming to study muscle contraction strategies that are used during different tasks and conditions. Most of SEMG simulators are based on energy modulation of a Gaussian noise. This work proposes a novel simulator in which the user-defined parameters are associated with the motor units (MUs) recruitment and their firing rate. Comparison between the mean spectrum of real SEMG signals collected in isometric contraction of the muscle biceps brachii and the mean spectrum obtained from simulated SEMG signals showed a good agreement, pointing the proposed simulator seems to be capable to generate consistent electromyographic signals in time and frequency domains and that can be used in many studies, in particular in the evaluation of automatic methods aimed to detect muscular contraction.     

Decomposition Approaches for Constrained Spatial Auction Market Problems

We consider several equilibrium formulations for the problem of managing spatially distributed auction markets of a homogeneous commodity, which are joined by transmission lines in a network. At each market, traders and buyers are determined by their price functions and choose their offer/bid values. We present equivalent variational inequality, optimization, and saddle point formulations of this problem. The corresponding models possess a special structure of constraint and cost functions and lead to different decomposition schemes. We propose proximal and splitting type methods and discuss their properties and preliminary computational results.     

Improving robustness of industrial object detection by automatic generation of synthetic images from CAD models

Object detection (OD) is used for visual quality control in factories. Images that compose training datasets are often collected directly from the production line and labeled with bounding boxes manually. Such data represent well the inference context but might lack diversity, implying a risk of overfitting. To address this issue, we propose a dataset construction method based on an automated pipeline, which receives a CAD model of an object and returns a set of realistic synthetic labeled images (code publicly available). Our approach can be easily used by non-expert users and is relevant for industrial applications, where CAD models are widely available. We performed experiments to compare the use of datasets obtained by the two different ways—collecting and labeling real images or applying the proposed automated pipeline—in the classification of five different industrial parts. To ensure that both approaches can be used without deep learning expertise, all training parameters were kept fixed during these experiments. In our results, both methods were successful for some objects but failed for others. However, we have shown that the combined use of real and synthetic images led to better results. This finding has the potential to make industrial OD models more robust to poor data collection and labeling errors, without increasing the difficulty of the training process.